MeshQu
https://www.meshqu.com

SITE SUMMARY
MeshQu is decision assurance infrastructure. It assesses consequential decisions against the policy an organisation has approved, makes the evidence and human authority behind them explicit, and keeps a signed Decision Receipt of each recorded assessment. Your systems control the action.

## Reviewed answers for agents

- [Knowledge index](https://www.meshqu.com/knowledge.json): Reviewed answers with claims, limitations, public sources and revision identifiers.
- [Reviewed answers](https://www.meshqu.com/knowledge): The same reviewed answers as web pages, one page per answer.
- [What a receipt records about who acted](https://www.meshqu.com/knowledge/actor-identity.json): Does a Decision Receipt prove who took the action?
- [AI agent governance, and bringing your own agent](https://www.meshqu.com/knowledge/ai-decision-accountability.json): How does MeshQu govern decisions an AI agent proposes, and can we use our own agent with it?
- [Decision chains: following a decision through reviews and the final call](https://www.meshqu.com/knowledge/decision-chains.json): How does MeshQu show a decision that took several steps, reviews and an exception?
- [Decision Receipts: what the record contains](https://www.meshqu.com/knowledge/decision-receipts.json): What is in a Decision Receipt, and what does it prove?
- [Enhanced due diligence decisions with MeshQu](https://www.meshqu.com/knowledge/enhanced-due-diligence.json): How does MeshQu support an enhanced due diligence (EDD) decision, and what does it not do?
- [Evidence, references and source custody](https://www.meshqu.com/knowledge/evidence-and-source-custody.json): What does MeshQu do with the evidence behind a decision, and does it establish that the evidence is true?
- [Human-in-the-loop automation with MeshQu](https://www.meshqu.com/knowledge/human-in-the-loop-automation.json): How can we automate checks in a review process while people keep authority over the decision?
- [Independent verification: the bundle, and what replay checks](https://www.meshqu.com/knowledge/independent-verification.json): How does someone independently verify a Decision Receipt, and what does replay check?
- [The limits of verification](https://www.meshqu.com/knowledge/limits-of-verification.json): What does verifying a Decision Receipt actually prove?
- [What a policy is, and how it is applied](https://www.meshqu.com/knowledge/policy-application.json): What is a policy in MeshQu, and how is it applied to a decision?
- [What a receipt evidences about a responsible-AI commitment](https://www.meshqu.com/knowledge/responsible-ai-evidence.json): Can a Decision Receipt show that an AI decision was fair, accurate or correct?
- [What MeshQu does](https://www.meshqu.com/knowledge/what-meshqu-does.json): What does MeshQu actually do?
- [What MeshQu is not](https://www.meshqu.com/knowledge/what-meshqu-is-not.json): What is MeshQu not, and which problems does it deliberately not solve?

## For agents and developers

- [MeshQu documentation](https://docs.meshqu.com): Concepts, guides and the API reference.
- [Documentation index for agents](https://docs.meshqu.com/llms.txt)
- [AI agent governance](https://www.meshqu.com/ai-decision-governance): Bring your own agent through MeshQu’s OAuth-secured MCP server or documented API.
- Availability: MeshQu is currently available for research, evaluation and design-partner deployments. Production availability and support commitments are agreed per engagement.

SITE STRUCTURE

Homepage:
- https://www.meshqu.com/

Platform:
- [Decision Receipts](https://www.meshqu.com/receipts): A Decision Receipt keeps the policy version, evidence references, actor and outcome behind each assessed decision, signed so it can be checked later.

Solutions:
- [AI agent governance and decision assurance](https://www.meshqu.com/ai-decision-governance): Govern AI agents at the point of decision. MeshQu makes rules, evidence and human authority explicit, and keeps a signed Decision Receipt of each assessment.
- [Human-in-the-loop automation](https://www.meshqu.com/human-in-the-loop-automation): Automate the checks in a review process while people keep authority over the decisions that matter. Start with the process you have and keep the evidence.
- [Enhanced due diligence](https://www.meshqu.com/enhanced-due-diligence): Make each enhanced due diligence decision easier to review and evidence: explicit rules, evidence by reference, recorded analyst judgement and approval.
- [APP reimbursement decisions](https://www.meshqu.com/app-fraud): Connect policy, evidence and authorised human judgement around APP fraud reimbursement reviews. Make the basis for each decision easier to explain.

Resources:
- [Journal](https://www.meshqu.com/blog): Essays, papers and news on decision receipts, evidence and agentic decisions.
- [Research](https://www.meshqu.com/research): Every MeshQu paper: three experiments on the same 283 UK procurement decisions, and the white paper that frames them.
- [Reviewed answers](https://www.meshqu.com/knowledge): The same reviewed answers as web pages, one page per answer.
- [AI governance frameworks: evidence for one decision](https://www.meshqu.com/topics/ai-governance-frameworks): AI governance frameworks say how decisions should be made. A Decision Receipt is a signed record, made at the time, of how one decision actually was made.
- [AI governance platforms and the record of each decision](https://www.meshqu.com/topics/ai-governance-platforms): AI governance platforms record how AI systems are governed. MeshQu adds a signed record of each consequential decision, made at the moment it happens.
- [AI governance policy: what one decision can show](https://www.meshqu.com/topics/ai-governance-policy): An AI governance policy says how decisions involving AI will be made. A few of its clauses can be shown to have held for one decision. This page is about those.
- [Responsible AI governance: what can be shown about one decision](https://www.meshqu.com/topics/responsible-ai-governance): Responsible AI governance makes commitments about how AI treats people. A few can be evidenced for one decision; most cannot. This page shows which is which.

Company:
- [Contact](https://www.meshqu.com/contact): Get in touch.

Legal:
- [Privacy](https://www.meshqu.com/privacy): How MeshQu handles personal data on meshqu.com: what we collect, why, who we share with, and your rights under UK GDPR.
- [Security](https://www.meshqu.com/security): MeshQu security posture: evidentiary integrity, tenant isolation, vulnerability disclosure, subprocessors, and SOC2 readiness.

Journal:
- [Article] [When an AI agent acts, what should you be able to prove?](https://www.meshqu.com/blog/agentic-ai-governance): A general statement about your AI governance process cannot answer why one payment was made, and neither can a test showing the agent usually behaves as expected. You need the evidence behind that particular decision: which policy applied, what was considered, what the checks returned and who approved it.
- [Article] [Europe, the UK and Singapore want the same record. What would it have to be?](https://www.meshqu.com/blog/three-regulators-one-unanswered-question): An EU policy process, UK public opinion and a Singapore legal working group have reached for the same requirement in three different vocabularies: the ability to establish, after the fact, what an automated system decided and on what basis. They agree on the need. None has yet said what form the answer should take.
- [News] [MeshQu selected to participate in the FCA Digital Sandbox](https://www.meshqu.com/blog/meshqu-selected-for-fca-digital-sandbox): MeshQu has been selected for the FCA Digital Sandbox. We will test a single claim against synthetic authorised push payment fraud data: that a challenged decision can be answered from a record made at the time, not reconstructed months later.
- [Article] [If two AI models read a policy the same way, will they decide the same way?](https://www.meshqu.com/blog/same-reasoning-different-decisions): We broke the previous experiment apart to find which piece was doing the work, then ran the same records through a second AI from a different company. The two models read the policy the same way and committed to verdicts on very different fractions of records.
- [Article] [What actually made an AI agent commit to a decision?](https://www.meshqu.com/blog/what-finally-changed-the-ais-mind): We ran the same AI over the same 283 UK procurement records five times, adding a layer of governance context each round. The decisive change was not more rules. It was being shown past decisions on similar cases, and that lever moved the agent in a single jump.
- [Article] [Why wouldn't the agent say no?](https://www.meshqu.com/blog/why-the-agent-wouldnt-say-no): An AI and a written rulebook reviewed the same UK government purchase records at the same moment. The AI named the same problems the rulebook did and almost never put a verdict on them. Changing the wording of one rule changed how often they agreed.
- [News] [The AI Act keeps moving. What happens to the decisions already made?](https://www.meshqu.com/blog/ai-act-still-moving-decisions-stand-still): The EU AI Act has been delayed again and its timelines are still being argued over. The decisions already made under it cannot move with them.
- [Article] [When a model explains a decision, what has it proved?](https://www.meshqu.com/blog/explainability-is-not-proof): AI explainability shows how a model behaved. It does not show which policy, threshold and model version were in force when the decision was made.
- [Article] [Which policy was in force when the decision was made?](https://www.meshqu.com/blog/policy-as-code-still-doesnt-solve-this): Policy-as-code evaluates a decision against the rules in force now. Showing which rules applied six months ago means capturing the decision as it is made.
- [Article] [When the FCA asks why one payment was cleared, what can you show?](https://www.meshqu.com/blog/the-problem-isnt-policy): A UK retail bank does not lack AI policy. It lacks decision proof for one cleared payment when an FCA review picks it out of a sample eight months later.
- [Article] [What does a decision look like when you can prove it?](https://www.meshqu.com/blog/what-a-decision-looks-like): A core banking platform reconstructs decisions after the fact; a provable decision is captured at execution instead, as a single signed artefact.
- [Article] [Why can't your logs explain the decision six months later?](https://www.meshqu.com/blog/from-archaeology-to-proof): Logs usually record what happened, rarely why. Decision proof means capturing the decision itself at execution rather than reconstructing it from fragments later.

Research:
- [Research paper] [Precedents, policy, and commitment](https://www.meshqu.com/research/precedents-policy-and-commitment): We re-ran the same procurement decisions through an AI agent with the governance context broken apart piece by piece — to find out which piece was doing the work.
- [Research paper] [When precedents commit AI and policy pulls it back](https://www.meshqu.com/research/when-precedents-commit-ai-and-policy-pulls-it-back): We showed one AI agent the same 283 UK procurement decisions five times, adding more of our governance rules each round — from nothing, up to the full policy.
- [Research paper] [When AI hedges and policy commits](https://www.meshqu.com/research/when-ai-hedges-and-policy-commits): We ran 283 real UK procurement decisions through both an AI agent and MeshQu’s policy engine at the same moment, binding every verdict to a signed receipt.
- [White paper] [The Decision Proof Gap](https://www.meshqu.com/research/decision-proof-gap): AI governance frameworks describe how decisions should be made — but the moment a decision is actually executed, the evidence to defend it almost never exists in a form anyone can verify.